A report from the United States Environmental Protection Agency (U.S. EPA) shows that people spend approximately 93% of their time indoors (house, school, office, stores etc.). Recently, accurate indoor localisation technologies have become available, making it possible to deploy at scale indoor Location-Based Services (LBS).
One key indoor LBS refers to tracking how people move throughout an indoor environment. This information, coupled with a model of the environment, can be used to derive useful analytics. Another key indoor LBS refers to tracking the position of portable assets in indoor environments. This can be used to, e.g., faster find such assets whenever needed or monitor their usage.
Such analytics offer benefits in a variety of areas including commercial, business, healthcare, corporate, security, government, science, and others. For example, retail stores and brick and mortar businesses have long desired to gather data that would allow them to better understand customer behaviour and how such behaviour is influenced by the salespersons. In hospitals, the analysis of location data can allow to optimise processes, while reducing costs and improving patient's safety. In environments characterised by safety and security concerns (e.g., chemical plants, offshore rigs) the analysis of location data can be used to monitor the respect of safety procedures and to detect potential risk situations. In manufacturing plants location data can be used to monitor deviation from processes and procedures, allowing a better usage of resources and increasing the overall productivity.
A need is felt for a solution that allows location data to be accurately analysed and indoor location data streams to be accurately segmented into specific segments, also called tracks, which are relevant for the understanding of specific subject's behaviour. For example, tracks can correspond to shopping sessions in a retail environment, to a shift of a given staff member in a health and care facility etc. This is fundamental for computing relevant information for the understanding and modelling of subject's behaviour in a given environment.
CN 105 260 901 A discloses an RFID-based intelligent store real-time data map system that ca be used in a physical store to effectively record and display real-time positions and moving tracks of customers and goods in the store and interaction conditions between the customers and the goods. The real-time data map system comprises a position data acquisition module, an interaction data acquisition module, a data storage and analysis module, and a data map display module, wherein the position data acquisition module is realized through an RFID reader capable of reading real-time two-dimensional coordinates of an RFID label, the interaction data acquisition module is realized through the RFID reader capable of reading RFID label information entering a view field, and the real-time positions of the customers and the goods are displayed on the map in real time via the data map display module. The data storage and analysis module analyses positions and interaction data of the goods and the customers, results are displayed on the map via the data map display module, and a report form is generated at the same time.